{"id":"W2293797001","doi":"10.3390/pr4010006","title":"Surrogate Models for Online Monitoring and Process Troubleshooting of NBR Emulsion Copolymerization","year":2016,"lang":"en","type":"article","venue":"Processes","topic":"Process Optimization and Integration","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Troubleshooting; Surrogate model; Copolymer; Emulsion; Process (computing); Process engineering; Computer science; Natural rubber; Biological system; Materials science; Polymer; Biochemical engineering; Chemical engineering; Engineering; Machine learning; Composite material","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004381839,0.0001063345,0.0001311806,0.00007616259,0.0000458381,0.00002016724,0.00006539621,0.00005030686,0.000004098643],"category_scores_gemma":[0.0001704278,0.00007879639,0.00001353604,0.0001887949,0.00002252304,0.0006551336,0.00000807448,0.00002595026,3.094578e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001405027,"about_ca_system_score_gemma":0.00002347565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000154286,"about_ca_topic_score_gemma":0.000003270025,"domain_scores_codex":[0.9994296,0.000003807006,0.0002190316,0.0001292413,0.00009483672,0.0001234562],"domain_scores_gemma":[0.9994486,0.00006237695,0.00006767164,0.0000552225,0.000330675,0.00003544689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002492531,0.0002347587,0.006169188,0.02087619,0.0001042554,4.375655e-7,0.003466082,0.4100558,0.2785841,0.001333738,0.00008045997,0.2788458],"study_design_scores_gemma":[0.0006646488,0.00004497105,0.00003435439,0.0005018962,0.00001683397,0.000001219722,0.0002281949,0.275453,0.7211557,0.001655337,0.00008574755,0.0001580694],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2332653,0.002675945,0.7631269,0.00007749802,0.0001139623,0.0002308729,0.00004251457,0.00023668,0.0002303589],"genre_scores_gemma":[0.9924836,0.001789099,0.005517872,0.000004507503,0.00006481457,0.00004720437,0.00002003161,0.00002738294,0.00004548089],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7592183,"threshold_uncertainty_score":0.3213224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02194193078598322,"score_gpt":0.2621965726650423,"score_spread":0.2402546418790591,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}